Forecasting interest rate volatility of the United Kingdom: evidence from over 150 years of data

Hossein Hassani; Mohammad Reza Yeganegi; Juncal Cuñado; Rangan Gupta

doi:10.1080/02664763.2019.1666093

Forecasting interest rate volatility of the United Kingdom: evidence from over 150 years of data

J Appl Stat. 2019 Sep 15;47(6):1128-1143. doi: 10.1080/02664763.2019.1666093. eCollection 2020.

Authors

Hossein Hassani¹, Mohammad Reza Yeganegi², Juncal Cuñado³, Rangan Gupta⁴

Affiliations

¹ Research institute for energy management and planning (RIEMP), University of Tehran, Tehran, Iran.
² Department of Accounting, Islamic Azad University Central Tehran Branch, Tehran, Iran.
³ University of Navarra, School of Economics, Pamplona, Spain.
⁴ Department of Economics, University of Pretoria, Pretoria, South Africa.

Abstract

This study examines the very short, short, medium and long-term forecasting ability of different univariate GARCH models of United Kingdom (UK)'s interest rate volatility, using a long span monthly data from May 1836 to June 2018. The main results show the relevance of considering alternative error distributions to the normal distribution when estimating GARCH-type models. Thus, we obtain that the Asymmetric Power ARCH (A-PARCH) models with skew generalized error distribution are the most accurate models when forecasting UK interest rates, while for the short, medium and long-term term forecasting horizons, GARCH models with generalized error distribution for the error term are the most accurate models in forecasting UK's interest rates.

Keywords: C22; C53; G17; GARCH models; Interest rates; error distributions; forecasting; volatility.

Grants and funding

Juncal Cuñado gratefully acknowledges financial support from the Ministerio de Economía y Competitividad (ECO2017-83183-R).